Data Structures for Big Data
Probabilistic & streaming data structures — Bloom filters, Count-Min Sketch, HyperLogLog, and other space-efficient structures that power analytics, deduplication, and real-time processing at scale.
Probabilistic Data Structures
Master Bloom filters, HyperLogLog, and Count-Min Sketch — memory-efficient structures that trade accuracy for performance at massive scale.
Bloom FiltersHyperLogLogCount-Min Sketch
Streaming Algorithms
Master streaming algorithms for real-time data processing — sliding window aggregation, Top-K heavy hitters, reservoir sampling, and min-heap ranking. Learn how to process unbounded data with bounded memory.
Sliding Window AggregationTop-K (Heavy Hitters)Reservoir SamplingMin-Heap for Top-K